Burton2000
commented
3 years ago You are trying to load the checkpoint from a previously trained model that was trained with 10 keywords so the output layer has a different number of neurons in it than the one with only 1 keyword.
Because the sizes of these final layers are different TensorFlow is not able to load the checkpoint. which is the error you get.
You can try passing skip_mismatch=True to the load weights call so hopefully TensorFlow will load all the weights it can and ignore the ones it can not.
Hi,
Why when I change the wanted words to only one word (yes for example) I get the following error
Traceback (most recent call last): File "test.py", line 199, in <module> test() File "test.py", line 44, in test model.load_weights(FLAGS.checkpoint).expect_partial() File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\keras\engine\training.py", line 2297, in load_weights status = self._trackable_saver.restore(filepath, options) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\tracking\util.py", line 1339, in restore checkpoint=checkpoint, proto_id=0).restore(self._graph_view.root) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\tracking\base.py", line 258, in restore restore_ops = trackable._restore_from_checkpoint_position(self) # pylint: disable=protected-access File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\tracking\base.py", line 978, in _restore_from_checkpoint_position tensor_saveables, python_saveables)) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\tracking\util.py", line 309, in restore_saveables validated_saveables).restore(self.save_path_tensor, self.options) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\saving\functional_saver.py", line 339, in restore restore_ops = restore_fn() File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\saving\functional_saver.py", line 323, in restore_fn restore_ops.update(saver.restore(file_prefix, options)) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\saving\functional_saver.py", line 116, in restore restored_tensors, restored_shapes=None) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\training\saving\saveable_object_util.py", line 132, in restore self.handle_op, self._var_shape, restored_tensor) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 308, in shape_safe_assign_variable_handle shape.assert_is_compatible_with(value_tensor.shape) File "C:\Users\ash_j\anaconda3\envs\newenvt\lib\site-packages\tensorflow\python\framework\tensor_shape.py", line 1161, in assert_is_compatible_with raise ValueError("Shapes %s and %s are incompatible" % (self, other)) ValueError: Shapes (3,) and (12,) are incompatible WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer.iter WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer.beta_1 WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer.beta_2 WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer.decay WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).layer_with_weights-0.kernel WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).layer_with_weights-0.bias WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).layer_with_weights-1.gamma WARNING:tensorflow:Unresolved object in checkpoint: (root).optimizer's state 'm' for (root).layer_with_weights-1.beta